2014
DOI: 10.1086/674008
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The Evolution of Age-Dependent Plasticity

Abstract: When organisms encounter environments that are heterogeneous in time, phenotypic plasticity is often favored by selection. The degree of such plasticity can vary during an organism's lifetime, but the factors promoting differential plastic responses at different ages or life stages remain poorly understood. Here we develop and analyze an evolutionary model to investigate how environmental information is optimally collected and translated into phenotypic adjustments at different ages. We demonstrate that plasti… Show more

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Cited by 97 publications
(155 citation statements)
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References 46 publications
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“…Gabriel, 1999;Relyea, 2003;Hoverman and Relyea, 2007). Such phenomena may also be age-dependent (Fischer et al, 2014). The significant difference in relative symphyseal cross-sectional area between the early and control groups at week 48 supports the idea of a time lag in reversing dietinduced changes during the second half of the experimental period.…”
Section: Discussionmentioning
confidence: 92%
See 1 more Smart Citation
“…Gabriel, 1999;Relyea, 2003;Hoverman and Relyea, 2007). Such phenomena may also be age-dependent (Fischer et al, 2014). The significant difference in relative symphyseal cross-sectional area between the early and control groups at week 48 supports the idea of a time lag in reversing dietinduced changes during the second half of the experimental period.…”
Section: Discussionmentioning
confidence: 92%
“…Although these studies have documented substantial variation in how plasticity varies with age, there appears to be a general tendency for plasticity to decrease as organisms mature. The reasons for this age-dependency are not clear, but it presumably results from several interacting factors, including, among others, the costs of plasticity, an organism's ability to detect and reliably interpret information about the environment (especially fluctuations) and lifehistory strategy (DeWitt et al, 1998;Hoverman and Relyea, 2007;Auld et al, 2010;Fischer et al, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…Importantly, the posterior distribution after one experience becomes the prior distribution for the next experience. This is why Bayesian approaches are useful for modeling development, where it is typical for a given individual to have a series of experiences over ontogeny, each of which may provide additional information about the state of the world (Frankenhuis and Panchanathan, 2011a,b;Fischer et al, 2014).…”
Section: Model Descriptionmentioning
confidence: 99%
“…When combined, these two assumptions allow us to model personality traits, which may be expressed soon after birth or hatching, and which usually vary continuously across individuals within populations. These assumptions set our model apart from other recent Bayesian models of development, which assume that (1) all of the individuals in a population are born with the same prior distribution, (2) the variable in the external world that animals are attempting to estimate can take on one of only two different states, and (3) there are only two phenotypes, each of which is favored in one of the two states (e.g., Frankenhuis and Panchanathan, 2011a;Fischer et al, 2014). In addition, our assumption that prior and posterior distributions are continuously distributed allows the means and the variances of these distributions to vary independently of one another (see below, Appendix and Discussion); this is not an option in twostate models, since in binomial distributions, the variance is a fixed function of the mean.…”
Section: Model Descriptionmentioning
confidence: 99%
“…Theoretical approaches may shed light on the complex evolutionary feedbacks that could result among these factors. Indeed, a recent model emphasizes the benefits to delaying trait development for a long enough period of time to obtain accurate information on the state of the environment (Fischer et al, 2014).…”
Section: The Complexities Of Developmentmentioning
confidence: 99%